easystats / easystats/performance
Expanded R2 measures for multilevel models
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Docs :books:
Enhancement :boom:
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- R
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Description
Nice framework for different components:
Rights & Sterba cannonical
A fixed-effects-only R-squared:
Edwards et al
Edwards et al. can be extended to GLMMs using quasi-likelihood:
r2glmm
Following up on https://github.com/easystats/performance/issues/332, it would also be good to have a nice vignette discussing R2 approaches for GL(M)Ms.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing issue #332 and the Rights & Sterba, Edwards et al., and r2glmm references linked here. Determine which expanded R2 measures should support multilevel and GL(M)M models, then add a vignette that compares the approaches and documents what is implemented.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- r
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100